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Michael Hess

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Michael Hess

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Publications by Michael Hess (bibliography)

» 2008 «

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Zhou, Daniel Xiaodan, Oostendorp, Nathan, Hess, Michael and Resnick, Paul (2008): Conversation pivots and double pivots. In: Proceedings of ACM CHI 2008 Conference on Human Factors in Computing Systems April 5-10, 2008. pp. 1009-1012. Available online

“Many sites on the web offer collaborative databases that catalog items such as bands, events, products, or software modules. Conversation pivots allow readers to navigate from pages about these items to conversations about them on the same site or elsewhere on the Internet. Double pivots allow readers to navigate from item pages to pages about other items mentioned in the same conversations. Using text mining techniques specific to the collection it is possible to find references to collected items in online conversations. We implemented conversation pivots for the CPAN archive of Perl modules, and for Drupal.org, the reference site for the Drupal content management system.”

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» 1992 «

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Hess, Michael (1992): An Incrementally Extensible Document Retrieval System Based on Linguistic and Logical Principles. In: Proceedings of the Fifteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 1992. pp. 190-197. Available online

“Most natural language based document retrieval systems use the syntax structures of constituent phrases of documents as index terms. Many of these systems also attempt to reduce the syntactic variability of natural language by some normalisation procedure applied to these syntax structures. However, the retrieval performance of such systems remains fairly disappointing. Some systems therefore use a meaning representation language to index and retrieve documents. In this paper, a system is presented that uses Horn Clause Logic as meaning representation language, employs advanced techniques from Natural Language Processing to achieve incremental extensibility, and uses methods from Logic Programming to achieve robustness in the face of insufficient data.”

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